Library
True to our non-profit nature, we believe in sharing our knowledge. We’re motivated by something greater than the bottom-line. We believe in supporting both the health of the education system in the United States and the well-being of each and every student. So we make a point to share what we learn with others who are positioned to make a difference, too.
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Estimating School Value-Added from Publicly Available Data: A Preliminary Investigation
In this research article from the "Applied Measurement in Education" Journal, EA staff members Michael Christian, Libby Pier, and Andrew Rice explore the possibilities for measuring school value-added using published data that are aggregated by school and grade as an option for situations in which student-level data are unavailable.
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Estimating School Value-Added from Publicly Available Data: A Preliminary Investigation
Stability of School Contributions to Student Social-Emotional Learning Gains
Recent attempts to measure schools’ influence on students’ social-emotional learning (SEL) show differences across schools, but whether these estimated differences measure the true effects of schools remain unclear. To better understand these measures, we examine the stability of estimated school-by-grade effects across two years using large-scale survey data.
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Stability of School Contributions to Student Social-Emotional Learning Gains
COVID-19 Impacts on Learning and Well-Being
This infographic highlights EA's research into changes in learning patterns experienced by students in grades 3–8 in California and South Carolina. Using results from winter 2020–21 interim assessments, EA provides an up-to-date picture of the learning lag students have experienced during the pandemic. EA also highlights findings from a well-being student survey collected during the 2020–21 school year.
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COVID-19 Impacts on Learning and Well-Being
COVID-19 Impacts on Student Learning: Evidence from Interim Assessments in California
We used data from interim assessments to examine how the rate of student learning from fall 2019 through winter 2020–21 differed from that of student learning before COVID-19 for approximately 100,000 students in grades 4-8 across 19 local education agencies in California. Results showed that students experienced approximately 2.5 months of learning lag on average in math and ELA, with more substantial learning lag for students who are economically disadvantaged, English Learners, and Latinx.
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COVID-19 Impacts on Student Learning: Evidence from Interim Assessments in California
Learning Change Models: Fall-to-fall and Fall-to-winter Results from South Carolina and California
In this document, we provide technical details on our learning change models, which estimate how much faster or slower students have grown during COVID-19. We also summarizes results from both fall-to-fall and fall-to-winter learning change models in South Carolina and California.
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Learning Change Models: Fall-to-fall and Fall-to-winter Results from South Carolina and California
Can We Measure Classroom Supports for Social-Emotional Learning?
We applied value-added models to student surveys in the CORE Districts to explore whether social-emotional learning (SEL) surveys can be used to measure effective classroom-level supports for SEL. We found that classrooms differ in their effect on students’ growth in self-reported SEL—even after accounting for school-level effects.
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Can We Measure Classroom Supports for Social-Emotional Learning?
School Differences in Social–Emotional Learning Gains: Findings From the First Large-Scale Panel Survey of Students
Using the first large-scale panel surveys of students on SEL, we produced school-level value-added measures by grade for growth mindset, self-efficacy, self-management, and social awareness. We found substantive differences across schools in SEL growth, with magnitudes of differences similar to those for growth in academic achievement, but weaker goodness of fit and smaller across-school variance, suggesting caution in interpreting such measures as causal impacts of schools on SEL.
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School Differences in Social–Emotional Learning Gains: Findings From the First Large-Scale Panel Survey of Students
The Influence of Rapidly Guessed Item Responses on Teacher Value-Added Estimates
We examined whether rapid guessing behaviors varied by grade, subject, and teacher, and we evaluated if rapid guessing influenced teacher value-added estimates. We found that rapid guessing occurs frequently enough that educators should be mindful of its effect on the interpretations of student test results, but rapid guessing did not appear to affect estimates of teacher performance.
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The Influence of Rapidly Guessed Item Responses on Teacher Value-Added Estimates
What We’ve Learned Building AI on Top of Education Data: Early Lessons From Piloting Stadium AI
At EA, we strive to build standard data infrastructure that democratizes data access, so educators can gain insights and improve student outcomes. In the age of AI, we are expanding that goal to cover not just data infrastructure, but “AI infrastructure” as well. That means building a system for AI-friendly context and deploying tools that utilize LLMs to answer prompts, so educators or agency staff who otherwise don’t have the time or technical expertise can access the data insights they need. We have built Stadium AI to test the hypothesis that a natural language interface on top of a well-structured education data warehouse could let more people, not just analysts, ask questions about their data and get answers they can trust. We started with testing a beta version of Stadium AI with real analyst users at the South Carolina Department of Education (SCDE) to see how they would use it, and if that could inform how a broader audience may use the tool. What we didn't expect? What users would ask when given the tool. In this blog, Technical Lead Manager Rob Little and Senior Product Manager Molly Stewart share what we've learned throughout the process of building Stadium AI.
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What We’ve Learned Building AI on Top of Education Data: Early Lessons From Piloting Stadium AI
Day in the Life: Q&A with Director of Services Tracy Diel
In this blog, Tracy describes her previous experience working in research, accountability, and assessment at Denver Public Schools, how her role as Director enables her to create the conditions for her team to do their best work, and her favorite partner projects to work on at EA.
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Day in the Life: Q&A with Director of Services Tracy Diel
EA Stack Series Part IV: Giving District Data a Platform with Podium with Katie O'Brien
April 17, 2026
In the latest episode of the DatabasED podcast, co-hosts Molly Stewart (Senior Project Manager) and Rosh Dhanawade (VP of Product) sit down with Katie O'Brien (Senior Product Manager) at Education Analytics to explore Podium, EA's data visualization platform built for education leaders.
Katie shares how Podium helps districts, schools, and state agencies answer the big questions they face every day, from tracking chronic absenteeism to understanding student behavior and enrollment trends. The conversation dives into how Podium's core dashboard suite provides quick, reliable insights while also giving districts the flexibility to build custom dashboards tailored to their unique initiatives.
The episode also unpacks the technical side of building a scalable business intelligence platform in education. Katie discusses how EA leverages tools like Apache Superset (via Preset), Ed-Fi data standards, and the Stadium data warehouse to deliver secure, multi-tenant data access across districts and states. She also highlights the challenges of adapting traditional BI tools for education use cases, including differences in school calendars, data privacy requirements, and complex user structures.
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EA Stack Series Part IV: Giving District Data a Platform with Podium with Katie O'Brien
Economists of Scale: Using Interoperability Technologies for Efficient Research with Large Datasets with Michael Christian and Sara Hu
January 28, 2026
In the latest episode of the DatabasED podcast, co-hosts Molly Stewart (Senior Product Manager) and Rosh Dhanawade (Vice President of Product) chat with Mike Christian, Principal Researcher, and Sara Hu, Research Scientist I, at Education Analytics. In this episode, Mike and Sara share how interoperability technologies are transforming research in the education sector. They also dive into their experiences using Ed-Fi data, Snowflake, SQL, and dbt documentation to conduct large-scale, efficient research at EA, along with the learning curve researchers face when moving from traditional flat files to modern data warehouses. This conversation highlights how bridging research, data engineering, and educational practice enables faster analysis, resulting in better outcomes for students and education stakeholders.
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Economists of Scale: Using Interoperability Technologies for Efficient Research with Large Datasets with Michael Christian and Sara Hu
AI’s Memory Capabilities Have Implications for K-12
September 25, 2026
In a webinar hosted by the American Enterprise Institute on September 24, 2026, panelists including Education Analytics’ CEO Andrew Rice, discussed the emerging challenges they face as artificial intelligence tools become capable of retaining information about students across interactions, and how states and other entities are dealing with the associated complexities of AI memory.
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AI’s Memory Capabilities Have Implications for K-12
Scott Bowers Joins Education Analytics’ Board of Directors
September 23, 2026
Education Analytics is pleased to announce the appointment of Scott Bowers to its board of directors. Bowers brings more than 35 years of executive leadership experience spanning finance, publishing, manufacturing, retail building materials, and advisory services, including prior roles as board chair, CEO, CFO, and publisher.
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Scott Bowers Joins Education Analytics’ Board of Directors
